Nondestructive Measurement System Research Articles

An Ultrasensitive Ti3C2Tx MXene-based Soft Contact Lens for Continuous and Nondestructive Intraocular Pressure Monitoring.

Wearable soft contact lens sensors for continuous and nondestructive intraocular pressure (IOP) monitoring are highly desired as glaucoma and postoperative myopia patients grow, especially as the eyestrain crowd increases. Herein, a smart closed-loop system is presented that combines a Ti3C2Tx MXene-based soft contact lens (MX-CLS) sensor, wireless data transmission units, display, and warning components to realize continuous and nondestructive IOP monitoring/real-time display. The fabricated MX-CLS device exhibits an extremely high sensitivity of 7.483mV mmHg-1, good linearity on silicone eyeballs, excellent stability under long-term pressure-release measurement, sufficient transparency with 67.8% transmittance under visible illumination, and superior biocompatibility with no discomfort when putting the MX-CLS sensor onto the Rabbit eyes. After integrating with the wireless module, users can realize real-time monitoring and warning of IOP via smartphones, the demonstrated MX-CLS device together with the IOP monitoring/display system opens up promising platforms for Ti3C2Tx materials as the base for multifunctional contact lens-based sensors and continuous and nondestructive IOP measurement system.

A Computer-Vision-Based Nondestructive Hairiness Measurement System on Yarn Cone Transportation Line

A Computer-Vision-Based Nondestructive Hairiness Measurement System on Yarn Cone Transportation Line

Validation of a Nondestructive Measurement System for Evaluating Surface Charge Distribution of Nonwoven Electret Fabrics

Validation of a Nondestructive Measurement System for Evaluating Surface Charge Distribution of Nonwoven Electret Fabrics

Design of Vivaldi antenna for non-destructive measurement applications

This paper presents an optimal dimension of the Vivaldi antenna design for the development of non-destructive measurement system applications. This project aims to design the Vivaldi antenna by investigating its design dimensions and analysing the antenna's performance in terms of return loss (S11), voltage standing wave ratio (VSWR), radiation pattern, and gain. The antenna is designed and fabricated using the FR-4 substrate as the dielectric substrate of the antenna, with a thickness of 1.5 mm (83.9 mm 7 80.6 mm 7 1.6 mm). As a result, the proposed design and fabricated antenna operate in the frequency range of 4.1 to 6 GHz with a return loss below -10 dB and VSWR between 1 and 2. The proposed design can transmit and receive the signal with directivity and gains of 6.8 dBi and 5.11 dBi, respectively.

Nondestructive measurement of anisotropic elastic constants of selective laser melted 316L based on a tri-mode ultrasonic method

Selective laser melting (SLM) technology can rapidly form metal parts with complex geometry, but the internal microstructure and material properties are significantly different from those of traditionally manufactured parts, such as obvious anisotropy and inhomogeneity. This paper proposed a tri-mode ultrasonic system to nondestructively measure the anisotropic elastic constants of 316L stainless steel prepared by SLM. Firstly, the quantitative relationship between ultrasonic wave velocities and anisotropic elastic constants was derived for elliptical anisotropic materials. The anisotropic elastic constants and Thomsen anisotropic parameters can be determined by measuring four ultrasonic wave velocities , , , and . Therefore, a tri-mode ultrasonic transducer was designed and fabricated to build the elastic constant ultrasonic measurement system. Then, the elastic constants and Thomsen anisotropic parameters of SLM samples were measured, and the key process parameters’ influence was discussed. The standard static tensile test validated the result of the ultrasonic test, and the maximum relative error was 6.94%. This study will provide a novel nondestructive measurement method and system of anisotropic elastic constants to ensure internal quality and improve the additive manufacturing process.

Non-destructive verification of materials in waste packages using QUANTOM®

The nuclear and non-nuclear industry has produced a considerable amount of low and intermediate-level radioactive wastes during the last decades. The material characterization of waste packages recently became more and more important in order to dispose of these waste packages in a final underground repository. Material characterization remains an indispensable criterion to prevent pollution of the groundwater with toxic materials and is usually required by the national licensing and supervisory authorities. Information on the nature of waste materials can be obtained based on existing documentation or, if the documentation is insufficient, on further destructive or non-destructive analysis. Non-destructive methods are to be preferred to minimize radiation exposures of operating personnel as well as costs. Existing non-destructive techniques (Gamma scanning, X-ray, active/passive neutron counting, muon tomography) do not allow the identification of non-radioactive hazardous substances. An innovative non-destructive measurement system called QUANTOM® (QUantitative ANalysis of TOxic and non-toxic Materials) has been developed. It is based on the prompt and delayed gamma neutron activation analysis (P&DGNAA). This technology is able to identify and quantify the elemental composition (Cd, Cu, B, Pb, Hg, Fe, Al, …) in radioactive packages such as 200-l radioactive drums. This information helps waste producers verify the content of their radioactive wastes, especially regarding the presence of hazardous substances. Different reference materials have been analysed by means of the same technology (P&DGNAA) at the research reactor of BUDAPEST. A comparison of those results for five reference materials is presented. The results show a very good agreement between QUANTOM® and standardized reference analyses.

Seasonality in Moisture Dynamics in the Walls of the rock-cut Churches in Lalibela, Ethiopia: Implications for Weathering

ABSTRACT Moisture plays a key role in rock decay in the built and natural environments. Rock-cut sites are particularly vulnerable to moisture-related weathering as they are carved into rock outcrops and do not have impermeable foundations or roofs to retard the flow of moisture. To characterise the moisture dynamics and its influence on weathering of rock-cut sites, we undertook a moisture monitoring campaign using a non-destructive Microwave Moisture Measurement System (MMMS) at two monolithic rock-cut churches in Lalibela, Ethiopia. The results showed that the walls were more saturated at depth than on the surface during the wet season. This suggests that low surface temperature and higher moisture content at depth will lead to constant-rate drying and accumulation of salts on the surface of the walls during the wet season. In the dry season, there was higher saturation near the surface than at depth (falling-rate drying). High rock surface temperature during the dry season contributes to subsurface drying and accumulation of salts below the surface. This seasonally shifting moisture dynamics will lead to a complex and dynamic damage profile. This study highlights the significant wetting facilitated by a lack of impermeable roofs and foundations at rock-cut structures during rainy periods.

A portable NIR system for nondestructive assessment of SSC and firmness of Nanguo pears

An accurate, nondestructive, and low-cost measurement system was developed using a portable near-infrared (NIR) spectrometer (DLP NIRscan Nano), a Raspberry Pi board, a display, a lithium battery, and a self-made three-dimensional printed shell. NIR data were collected through two measurement modes (column and Hadamard transform) based on digital light processing. With this equipment, detection models of soluble solid content (SSC) and firmness, essential quality indicators of the fruit, were established via quantitative analysis using chemometrics and a hybrid wavelength selection strategy. The SSC and firmness prediction model established through the combination of the synergy interval partial least squares and genetic algorithm (Si-GA-PLS) showed higher prediction accuracy, with coefficient of determination of prediction (RP2) values of 0.9406 and 0.9119, respectively, and root-mean-square error of prediction (RMSEP) values of 0.1655 and 5.5003, respectively. A comparison of the model performance of different monochromator principles was also explored; they were found to be non-statistically significant differences from one another. Finally, data fusion was used to improve prediction ability. The results obtained by mid-level data fusion presented a better performance than using models based on one technique. Overall, the developed novel handheld detector exhibits potential for smart software applications with high accuracy.

Application of image processing and soft computing strategies for non-destructive estimation of plum leaf area.

Plant leaf area (LA) is a key metric in plant monitoring programs. Machine learning methods were used in this study to estimate the LA of four plum genotypes, including three greengage genotypes (Prunus domestica [subsp. italica var. claudiana.]) and a single myrobalan plum (prunus ceracifera), using leaf length (L) and width (W) values. To develop reliable models, 5548 leaves were subjected to experiments in two different years, 2019 and 2021. Image processing technique was used to extract dimensional leaf features, which were then fed into Linear Multivariate Regression (LMR), Support Vector Regression (SVR), Artificial Neural Networks (ANN), and the Adaptive Neuro-Fuzzy Inference System (ANFIS). Model evaluation on 2019 data revealed that the LMR structure LA = 0.007+0.687 L×W was the most accurate among the various LMR structures, with R2 = 0.9955 and Root Mean Squared Error (RMSE) = 0.404. In this case, the linear kernel-based SVR yielded an R2 of 0.9955 and an RMSE of 0.4871. The ANN (R2 = 0.9969; RMSE = 0.3420) and ANFIS (R2 = 0.9971; RMSE = 0.3240) models demonstrated greater accuracy than the LMR and SVR models. Evaluating the models mentioned above on data from various genotypes in 2021 proved their applicability for estimating LA with high accuracy in subsequent years. In another research segment, LA prediction models were developed using data from 2021, and evaluations demonstrated the superior performance of ANN and ANFIS compared to LMR and SVR models. ANFIS, ANN, LMR, and SVR exhibited R2 values of 0.9971, 0.9969, 0.9950, and 0.9948, respectively. It was concluded that by combining image analysis and modeling through ANFIS, a highly accurate smart non-destructive LA measurement system could be developed.

Optical nondestructive evaluation for minor debonding defects and interfacial adhesive strength of solid propellant

Minor debonding defects and weak adhesion impair solid propellant integrity, which may cause rocket launch failure. However, it’s difficult to identify these interfacial bonding problems in-situ by the common temporal phase-shifting method due to its inaccurate phase calculation and background noises. In this work, a real-time phase processing method with high-frequency synchronizing trigger technology is proposed to improve phase map quality and anti-interference performance in the phase-shifting process. The method is applied to shearography/ESPI optical nondestructive measurement systems to detect minor debonding defects with minimum diameter of 2 mm and evaluate interfacial adhesive strengths of the bonding layers, respectively. The results show that stable and high-contrast phase maps are obtained in real-time from a large field of view, indicating that the detection capabilities of shearography/ESPI are enhanced via the application of the method. This work would contribute to the in-situ nondestructive evaluation of minor defects and weak adhesion in solid propellants.

Adaptive Under-Sampling Deep Neural Network for Rapid and Reliable Image Recovery in Confocal Laser Scanning Microscope Measurements

Confocal laser scanning microscopy (CLSM) is a non-destructive optical measurement system of high precision, applicable to the construction of three-dimensional (3-D) topographies of biological cells and engineered materials at the micro- and sub-micro scales. Compressive sensing (CS) has recently been applied in microscope systems to reduce the amount of sampled data required for the reconstruction of images; however, the iterative nature of the CS recovery algorithm imposes high computational complexity. This article presents an end-to-end non-iterative deep residual convolutional neural network (CNN) applicable to CLSM systems for CS-based reconstruction. In experiments and numerical simulations, the proposed scheme outperformed the existing CS recovery algorithms in terms of reconstructed image quality and computation time. The proposed algorithm also enabled the reconstruction of images using samples obtained in different regions of an image at various sampling rates to overcome nonuniform information density. The reconstruction performance of the model in terms of robustness and efficiency was validated using real-world CLSM data obtained via random scanning patterns.

Wi-Fruit

People usually assess fruit qualities from external features such as color, shape, size, and texture. However, it is quite common that we select fruits with perfect appearances but rotten inside, especially for fruits with thick pericarps. Thus the accurate measurement is desirable to evaluate the internal conditions of fruits. As two key features of fruit internal qualities, existing methods on measuring fruit moisture and soluble solid contents (SSC) are either destructive or costly, limiting their adoption in daily life. In this paper, we propose Wi-Fruit, a non-destructive and low-cost fruit moisture and SSC measurement system leveraging Wi-Fi channel state information (CSI). First, to cope with the fruit structure dependency challenge, we propose a double-quotient model to pre-process CSI on adjacent antennas. Second, to address the fruit size and type dependency challenges, a lightweight artificial neural network (ANN) model with visual information fusion is proposed for fruit moisture and SSC estimations. Extensive evaluations are conducted on 6 types of fruits with both thick (i.e., watermelon and grapefruit) and thin pericarps (i.e., dragon fruit, apple, pear, and orange) over a month in either an empty laboratory room or a library with massive books. Results demonstrate that Wi-Fruit achieves an acceptable estimation accuracy (RMSE=0.319). It is independent of various fruit structures, sizes, and types, while also robust to time and environmental changes. The fruit internal sensing capabilities of Wi-Fruit can help fruit saving and safety in both pre-harvest and post-harvest applications.

구조파를 이용한 볼트부 축력 비파괴측정 시스템 연구

구조파를 이용한 볼트부 축력 비파괴측정 시스템 연구

Nondestructive Detection and Analysis of Skidding Damage for Bearing Steel 100Cr6 Using Improved Magnetic Barkhausen Noise Technique

Skidding damage, which extensively appears in the bearings at a high rotation speed, often shortens the lifetime of bearings and even induces the total failure of the bearings. This paper proposes a novel nondestructive measurement system for evaluating the degree of skidding damage by using the improved magnetic Barkhausen noise (MBN) technique. A ring-type probe with a bias current is designed to capture the weak MBN signal generated from the narrow section in the ferromagnetic material. It can increase the detection resolution of skidding damage compared to the commonly employed cylindrical probe. The excitation frequency of the electromagnetic field is optimized to enhance the strength of the MBN signal, and the background noise is suppressed by a bandpass filter. One sample with different degrees of skidding damage is prepared and detected. Experiments demonstrate that the skidding damage can suppress the generation of the MBN signal in the sample, and the peak amplitude of the MBN signal envelope gradually declines with the increase in the degree of skidding damage. These indicate that the skidding damage on the bearing steel can be evaluated by the proposed measurement system.

Measurement Method Based on Multispectral Three-Dimensional Imaging for the Chlorophyll Contents of Greenhouse Tomato Plants.

Nondestructive plant growth measurement is essential for researching plant growth and health. A nondestructive measurement system to retrieve plant information includes the measurement of morphological and physiological information, but most systems use two independent measurement systems for the two types of characteristics. In this study, a highly integrated, multispectral, three-dimensional (3D) nondestructive measurement system for greenhouse tomato plants was designed. The system used a Kinect sensor, an SOC710 hyperspectral imager, an electric rotary table, and other components. A heterogeneous sensing image registration technique based on the Fourier transform was proposed, which was used to register the SOC710 multispectral reflectance in the Kinect depth image coordinate system. Furthermore, a 3D multiview RGB-D image-reconstruction method based on the pose estimation and self-calibration of the Kinect sensor was developed to reconstruct a multispectral 3D point cloud model of the tomato plant. An experiment was conducted to measure plant canopy chlorophyll and the relative chlorophyll content was measured by the soil and plant analyzer development (SPAD) measurement model based on a 3D multispectral point cloud model and a single-view point cloud model and its performance was compared and analyzed. The results revealed that the measurement model established by using the characteristic variables from the multiview point cloud model was superior to the one established using the variables from the single-view point cloud model. Therefore, the multispectral 3D reconstruction approach is able to reconstruct the plant multispectral 3D point cloud model, which optimizes the traditional two-dimensional image-based SPAD measurement method and can obtain a precise and efficient high-throughput measurement of plant chlorophyll.

Simulation study on the design of nondestructive measurement system using fast neutron direct interrogation method to nuclear materials in fuel debris

ABSTRACT In order to measure the amount of nuclear materials in the fuel debris produced in the Fukushima Daiichi Nuclear Power Plant accident, we have designed a measurement system based on a Fast Neutron Direct Interrogation (FNDI) method. In particular, we have developed a fast response detector bank for fast neutron measurements by Monte Carlo simulations. The new bank has more than one order of magnitude faster response compared to the standard ones. We have also simulated the nondestructive measurements of the nuclear materials in homogeneously mixed fuel debris with various matrices which contain stainless steel (JIS SUS304), concrete, and various control-rod (CR) contents in the designed system. The results show that if the debris contains less than 1.0 vol% of CR component and more than 2.5 vol% of spent fuel component, the fissile materials in the debris can be measured by using the designed system.

Simultaneous Measurement of MDL and DMGD in FMFs by Analyzing the Rayleigh Backscattering Amplitudes

In this paper, we propose and experimentally demonstrate a novel method for simultaneously measuring mode-dependent loss (MDL) and differential modal group delay (DMGD) in few mode fibers (FMFs). This method is based on analyzing the Rayleigh backscattering amplitudes obtained with a special nondestructive measurement system. With this method, the MDL and DMGD in about 9.8 km 3-mode fiber are successfully measured, which are 0.186 dB and 3.581 ps/m between LP 01 and LP 11a and 0.157 dB and 3.604 ps/m between LP 01 and LP 11b , respectively. Then, the experimental results of DMGD and MDL with different methods are compared, which show that the values of DMGD and MDL obtained by the proposed method agree well with that using the time-of-flight (TOF) and conventional transmission methods, respectively. In addition, it is also demonstrated that the proposed scheme can be scalable to measure FMFs with a large number of modes.

Significant dynamic range and precision improvements for FMF mode-coupling measurements by utilizing adaptive wavelet threshold denoising

In this paper, we propose and experimentally demonstrate a measurement method of mode coupling in few-mode fiber (FMF) based on adaptive wavelet threshold denoising. A nondestructive measurement system of mode coupling along an FMF is established to verify the performance of our proposed method. The system consists of a mode transverter (Photonic Lantern A), a mode demultiplexer (Photonic Lantern B), an FMF circulator and so on Experimental results show that, compared with the results obtained by the average time/number denoising of traditional optical time domain reflectometry (OTDR), the dynamic ranges of backscattered power of the excitation mode LP01, LP11a and LP11b are respectively increased by 3.72 dB, 3.43 dB and 3.37 dB with adaptive wavelet threshold denoising, and correspond to the dynamic ranges of the non-excitation mode are also improved. Moreover, the proposed technique effectively reduce the amplitude fluctuation of the backscattered power distribution of LP01, LP11a and LP11b modes, and thus the measurement accuracy of mode coupling coefficients are averagely raised by 2.62 dB/km between LP01 and LP11a, and 1.51 dB/km between LP01 and LP11b, respectively. We confirm that the dynamic range and measurement precision of mode-coupling are effectively improved.

Dielectric and Bioimpedance Research Studies: A Scientometric Approach Using the Scopus Database

This work describes the worldwide applications of dielectric and bioimpedance measurements techniques in various fields. Dielectric and bioimpedance spectroscopy are major non-destructive measurement systems with great potential in the technology field. All results produced by the Scopus database were used as the core of the study in hand, with different items from journals, papers and conference proceedings being taken into account. The results of this analysis show that the interest in electrical properties has risen in the last years due to the advanced technological measurements offered on the scientific level. Results show that bioimpedance studies are considerably more recent compared to dielectric studies, and are more directed towards medical purposes while dielectric spectroscopy focuses on physical aspects, and is used mostly in engineering and material science. It can be stated that bioimpendance and dielectric spectroscopy are being increasingly applied and that they have the capacity to deepen and enhance research investigation.

A high accuracy ultrasonic measurement system using the prism technique

In this paper, a non-destructive measurement system is proposed to evaluate the elastic properties of highly attenuating homogeneous and non-homogeneous materials. This measurement system is based on a mode conversion technique allowing the evaluation of both compressional (P) and shear (S) waves with only one transducer. In the experimental investigation, the specimen under test (SUT), realized in a prism-shaped form, is tested using the prism technique. Then, the gathered backscattered echoes are estimated using a model-based estimation algorithm in order to extract the desired elastic properties. Accordingly, the estimated parameters are in good agreement with the manufactured values, which demonstrates the effectiveness of the proposed measurement system, and therefore, can be considered as a promising way to robustly evaluate certain properties of highly attenuating materials.